CXO INSIGHT December2025

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THE YEAR’S BIG TECH MOMENTS

ISSUE 81 \ DECEMBER 2025

SPOTLIGHT

SENTINELONE:

The new cybersecurity reality

AWS RE:INVENT 2025

THE POWER STACK

Vertiv’s Giordano Albertazzi on the next era of AI-ready digital infrastructure

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18 COVER FEATURE

THE POWER STACK

Vertiv CEO Giordano Albertazzi on the shifts redefining digital infrastructure in the age of AI

SPOTLIGHT 36 RUNNING THE NEW FRONTIER Key takeaways from AWS re:Invent 2025

INTERVIEWS 26 AFTER THE PILOT Dataiku’s Kurt Muehmel on why enterprise AI success depends on how systems are governed, monitored, and designed to operate at scale 46 SECURING THE DIGITAL MOMENTUM Netskope’s Steve Riley on how SASE and Zero Trust are reshaping enterprise security to balance innovation, governance, and control

VIEWPOINTS 43 A STRATEGIC IMPERATIVE, NOT A COST Cisco on why AI-ready networking must be treated as a national and enterprise priority, not an IT expense

36

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44 THE NEW CYBERSECURITY REALITY SentinelOne highlights the shifts reshaping defence in 2026

44 WHAT’S NEW 50 The latest gears and gadgets to keep you ahead of the curve

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DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

3

EDITORIAL

TURNING POINT As 2025 comes to a close, the tone of the technology conversation has changed. Early in the year, experimentation still dominated — pilots, sandboxes, and proof-of-concepts presented as progress. Those gestures were no longer enough. Boards, regulators, and customers were asking a simpler, tougher question: what is actually running — and what value is it delivering?

This final issue of 2025 reflects that shift. The year marked a move from enthusiasm to expectation, and from experimentation to operational reality. AI, cloud, and data stopped being treated as innovation layers and started being judged as core systems — subject to the same scrutiny as any other part of the enterprise.

Cost control, resilience, governance, and reliability moved to the foreground. Execution became the measure of credibility.

That perspective underpins our cover story, which features Vertiv’s Giordano Albertazzi and examines how AI is reshaping the physical foundations of digital infrastructure. He notes how AI has pushed infrastructure demands into a new category of urgency, and that traditional architectures no longer match current workloads. His emphasis on systems needing to remain productive for many years, despite rapidly changing requirements, supports this framing.

The same reality played out at AWS re:Invent 2025, which CXO Insight ME covered in Las Vegas. The tech giant clearly pointed out how AI has moved out of the lab. The focus has shifted to what happens when these systems are expected to run continuously, inside regulated environments, under real operational constraints.

This issue also features perspectives from Cisco, Netskope, Confluent, and Dataiku, among others, who offer insights on how to move AI beyond pilots, how security and governance are being rethought, how realtime data is becoming foundational, and how workforce dynamics are evolving under growing pressure.

What is changing now is not the ambition of organisations, but their expectations of technology.

As 2026 approaches, the defining skill will be discernment — knowing where technology belongs in the business, and where it does not.

Happy reading!

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Adelle Geronimo Managing Editor

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DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

5

IN OUR RADAR

UAE women leaders show strong optimism on AI leadership equality

Abu Dhabi’s Integrated Transport Centre has launched a pilot autonomous delivery service with noon and AutoGo – a subsidiary of K2, deploying AI-powered self-driving vehicles to support e-commerce logistics as part of the emirate’s smart, sustainable mobility strategy.

A Cloudera survey reveals that 91 percent of women leaders in the UAE are optimistic about achieving gender equality in AI leadership, highlighting growing confidence in inclusive AI strategies, leadership opportunities, and the country’s broader push toward equitable digital transformation.

First commercial science satellite in orbit

xAI secures $15 billion to accelerate AI ambitions

London-based Blue Skies Space has launched Mauve, the world’s first private space science satellite, now in orbit studying stellar flares and exoplanets. The microwave-sized satellite will share its data with global research institutions through a commercial subscription model.

Elon Musk’s artificial intelligence startup, xAI, has raised $15 billion in a new funding round, underlining strong investor confidence as the company scales its AI models, infrastructure, and competition with established generative AI leaders.

OPSWAT strengthens regional leadership with new MENA VP

Confluent appoints new regional head for the Middle East

kavi designs / Shutterstock.com

Abu Dhabi takes autonomous delivery to the streets

OPSWAT has appointed Hussam Sidani as Vice President for the Middle East and North Africa, reinforcing its commitment to regional growth.

The move underscores OPSWAT ’s focus on expanding partnerships, strengthening customer engagement, and scaling critical infrastructure protection across the region.

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CXO INSIGHT MIDDLE EAST | DECEMBER 2025

Confluent has appointed Karim Azar as Area Vice President and General Manager for the Middle East, reinforcing its regional leadership bench as demand for real-time data streaming grows across enterprises accelerating cloud and digital transformation initiatives.

NEWS

UAE completes first government transaction using Digital Dirham

The Ministry of Finance and Dubai Finance (DOF) have completed the United Arab Emirates’ first government financial transaction using the Digital Dirham, in collaboration with the Central Bank of the UAE.

The transaction was executed in November 2025 as part of the pilot phase of the Digital Dirham project, launched under the Financial Infrastructure Transformation (FIT) Programme with local financial authorities.

The move forms part of broader efforts to expand the use of digital payments and support the adoption of the national digital currency across government and private sector operations.

The pilot transaction was conducted using the mBridge platform, developed by the Central Bank to enable secure settlement of central bank digital currencies (CBDCs) between government entities. The test focused on technical integration and operational readiness, with the transaction completed in less than two minutes.

The use of the Digital Dirham for government transactions is a qualitative shift in leveraging financial technology, creating an opportunity to develop government and private payments HE MOHAMMED HADI AL HUSSEINI Minister of State for Financial Affairs

The Digital Dirham initiative is part of the UAE’s wider financial infrastructure strategy aimed at improving efficiency, transparency, and the integration of national financial systems.

Emirates Group brings ChatGPT Enterprise into core operations

(LtoR) Ali Serdar Yakut, Emirates Group, and Rod Solaimani, OpenAI

Emirates Group has announced a collaboration with OpenAI to accelerate the adoption of generative artificial intelligence across its operations, focusing on enterprise-wide deployment and innovation.

Under the agreement, Emirates Group will roll out ChatGPT Enterprise across the organisation, supported by AI literacy programmes, technical exploration, and executive alignment aimed at 8

CXO INSIGHT MIDDLE EAST | DECEMBER 2025

embedding AI capabilities across business functions. The initiative also includes plans to establish an internal network of AI champions and an AI Centre of Excellence to support practical use cases.

Ali Serdar Yakut, Executive Vice President IT, Emirates Group, said, “We see enormous potential for AI

technology to support our business requirements, helping us tackle complex commercial challenges, strengthening our operations, and enhancing the customer experience. Closely working with OpenAI will make our technology investments both strategic and scalable, enabling us to deliver enhanced value to our employees and customers, fundamentally changing how we innovate, deliver value, and maintain our competitive edge in the industry.”

Rod Solaimani, Regional Director for MENA and Central Asia, OpenAI, said, “Emirates Group has laid out a bold vision for how AI can transform the future of aviation. With this collaboration, we’re proud to help them bring that vision to life, embedding intelligence across their operations, empowering teams with powerful new tools, and reimagining the travel experience for millions of customers.”

The collaboration will be implemented in phases, with a focus on responsible deployment, data protection, and alignment with the UAE’s national AI strategy.

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NEWS

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Aramco and PASQAL deploy Saudi Arabia’s first quantum computer

Aramco has announced the deployment of Saudi Arabia’s first quantum computer in collaboration with French quantum

computing company PASQAL, marking a milestone in the Kingdom’s advanced computing capabilities.

The system, a quantum computer based on neutral atom technology, has been installed at Aramco’s facilities and will be used to support research into complex industrial and scientific challenges. According to the companies, the technology is expected to accelerate progress in areas such as materials science, optimisation, and energy-related applications.

The initiative forms part of Aramco’s broader efforts to explore next-generation computing technologies and strengthen local research and development capabilities. It also aligns with Saudi Arabia’s national ambitions to build expertise in emerging technologies and expand its innovation ecosystem.

PASQAL’s quantum platform enables the simulation of highly complex systems that are difficult to model using classical computers, allowing researchers to test new approaches to problem-solving at scale.

IBM has agreed to acquire data infrastructure company Confluent in a deal valued at approximately $11 billion, according to Reuters, as the company moves to strengthen its cloud computing and artificial intelligence capabilities.

Under the terms of the agreement, IBM will pay $31 per share in cash, representing a significant premium to Confluent’s recent trading price. The transaction has been approved by the boards of both companies and is subject to regulatory approvals and Confluent shareholder consent.

Confluent is best known for its data streaming platform built around Apache Kafka, which enables organisations to process and manage real-time data across distributed systems. According to Reuters, IBM sees the acquisition as

IBM plans to fund the Confluent deal in cash, targeting a mid-2026 close

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CXO INSIGHT MIDDLE EAST | DECEMBER 2025

Framalicious / Shutterstock.com

IBM to acquire Confluent in $11 billion cloud computing deal

a way to enhance its ability to connect, process, and govern data across hybrid and multi-cloud environments, a key requirement for enterprise AI deployment.

The deal is expected to close in the first half of 2026. Confluent shares rose

sharply following the announcement, while IBM shares were little changed.

The acquisition is IBM’s largest software deal in several years and reflects growing demand for real-time data infrastructure as enterprises scale cloud and AI workloads.

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NEWS

G42 receives US approval for advanced AI chip exports Abu Dhabi-based technology company G42 has received approval from the United States government to import advanced artificial intelligence semiconductors, marking a significant development in UAE–US technology cooperation.

The approval enables the export of high-end AI chips to G42 to support large-scale computing initiatives underway in the UAE. These include the Stargate UAE project, a onegigawatt AI compute cluster being developed as part of a broader five-gigawatt AI infrastructure hub designed to provide regional computing capacity.

According to the announcement, the advanced chips will support G42’s expansion of foundational AI infrastructure and deepen collaboration with US technology partners, including hyperscalers and semiconductor companies. Deployment of the chips

will be governed by a regulated technology and compliance framework overseen by US authorities.

G42 operates several highperformance computing systems that are ranked among the world’s Top

500 supercomputers. The approval is expected to strengthen the UAE’s position in secure, large-scale AI infrastructure development and support the country’s ambitions in advanced computing and artificial intelligence.

KAUST unveils Middle East’s most powerful supercomputer With Shaheen III, Saudi Arabia stands at the forefront of computation-driven discoveries and impact PROFESSOR SIR EDWARD BYRNE President, KAUST

King Abdullah University of Science and Technology (KAUST) has unveiled the most powerful supercomputer in the Middle East, strengthening Saudi Arabia’s high-performance computing capabilities and research infrastructure.

The new system is designed to support advanced scientific research across areas including artificial intelligence, climate modelling, energy systems, materials science, and biosciences. According to the university, the supercomputer

significantly expands KAUST’s ability to process large-scale datasets and run complex simulations that are not feasible on conventional computing platforms.

The deployment forms part of KAUST’s broader investment in research infrastructure to support national priorities in science, technology, and innovation. It also aligns with Saudi Arabia’s wider ambitions to build advanced digital and research capabilities under Vision 2030.

KAUST is currently ranked as the top Arab university globally, and the new supercomputing system is expected to support collaboration with academic, industry, and government partners both within the Kingdom and internationally.

The system will be made available to researchers at KAUST and select collaborators, supporting projects that require large-scale computational power and accelerating research outcomes across multiple disciplines.

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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QUOTEWORTHY

“DUBAI IS ESTABLISHING INSPIRING MODELS FOR THE WORLD BY CREATING AN ENABLING ENVIRONMENT THAT ATTRACTS AND EMPOWERS TALENT, INSPIRING ONE AND ALL TO PURSUE A PROMISING FUTURE DRIVEN BY KNOWLEDGE, CREATIVITY, AND INNOVATION” HH Sheikh Hamdan bin Mohammed bin Rashid Al Maktoum, Crown Prince of Dubai, Deputy Prime Minister and Minister of Defence of the UAE, and Chairman of The Executive Council of Dubai

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CXO INSIGHT MIDDLE EAST | DECEMBER 2025

“THE TRUE VALUE OF AI HAS NOT YET BEEN UNLOCKED… WE BELIEVE THE ADVENT OF AI AGENTS HAS BROUGHT US TO AN INFLECTION POINT” Matt Garman, CEO, Amazon Web Services

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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REPORT

FOMO AT WORK:

THE OPPORTUNITY GAP IN TECH 16

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A

persistent opportunity gap continues to shape women’s careers in technology, influenced by bias, uneven access to leadership pathways, and the cumulative pressure of balancing professional ambition with personal responsibility.

That is the central finding of Acronis’ 2025 Women in Tech Report, “FOMO at Work: The Opportunity Gap Between Men and Women in Tech,” which examines how men and women perceive career progression, opportunity, and barriers across the global technology sector.

Based on a global survey of more than 650 IT professionals, the research reveals a clear perception divide. Men are significantly more likely to view the industry as equitable, while women consistently report structural and cultural obstacles that affect their ability to advance. The gap is not one of motivation or capability, but of access — to development opportunities, leadership exposure, and organisational environments that account for real-world demands.

Only 60 percent of women believe men and women have equal access to career development and growth, compared with 75 percent of men. This divergence extends into daily working realities.

Nearly two-thirds of women say work–life balance challenges have a significant impact on women’s career progression, a view shared by fewer than half of men. The expectation of long working hours also weighs more heavily on women, with a greater proportion believing that putting in extra time is necessary simply to remain competitive.

Bias remains a defining factor, particularly in cybersecurity and leadership pathways. Women are more likely than men to cite stereotypes as a barrier to entering the sector and progressing into senior roles. These perceptions shape career trajectories early, influencing confidence, visibility, and long-term retention, rather than emerging only at the point of promotion.

The report also captures the psychological dimension of inequality.

More than half of women surveyed say they are very or extremely concerned about missing career opportunities because of family responsibilities, compared with 42 percent of men. This persistent fear of being absent at critical moments — whether meetings, projects, or informal networks — creates an additional layer of risk that influences how women engage with opportunities and plan their careers.

“Our new survey findings shine a spotlight on just how differently men and women experience working in the tech industry,” said Alona Geckler, SVP Business Operations and Chief of Staff at Acronis. “Closing the gender gap requires more than good intentions.

Organisations must recognise these disparities and design programs that expand leadership opportunities, confront bias head-on, and create environments where work-life balance doesn’t present any barriers that may potentially derail women’s careers.”

Women’s responses point towards practical interventions rather than abstract commitments. Leadership development programmes tailored to women are prioritised far more highly by female respondents, signalling demand for structured pathways and advocacy. Men, meanwhile, tend to underestimate the scale and persistence of systemic barriers, highlighting a continued disconnect that organisations must address if inclusion strategies are to be effective.

With women representing just 29 percent of the global tech workforce, the findings underline a challenge the industry has yet to resolve. The opportunity gap is not theoretical. It is embedded in how careers are structured, supported, and evaluated — shaping who advances, who leads, and who is forced to weigh professional progress against personal cost.

60%

The share of women who believe career opportunities in tech are equal, compared with 75% of men

63%

The proportion of women who say work–life balance limits career progression, versus 49% of men

41%

The share of women who identify bias as the biggest barrier to pursuing leadership roles in tech

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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COVER FEATURE

THE POWER STACK Giordano Albertazzi, CEO, Vertiv, discusses the shifts redefining digital infrastructure as AI drives unprecedented demand for power and density—and what it will take to build systems ready for the next era of compute

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COVER FEATURE

D

igital infrastructure is being reshaped by a series of converging demands: higher power loads, increased heat density, compressed deployment timelines and the need for predictable longterm performance. These pressures existed before artificial intelligence began accelerating, but AI has pushed them into a new category of urgency. Data-centre operators, cloud providers and governments now treat infrastructure planning as a central pillar of their technology ambitions, and the expectations placed on facility design have expanded accordingly.

“Infrastructure has to support technology that is evolving quickly,” says Giordano Albertazzi, CEO of Vertiv. “The systems we build now must remain productive and resilient for many years.”

Global data centre capacity is undergoing a rapid, high-density expansion, driven by cloud platforms, national digital programmes, and the accelerating demand for Generative AI workloads. Gartner forecasts worldwide spending on Data Centre Systems alone to exceed US$405 billion in 2025, representing a 23.2 percent growth year-on-year. Further magnifying this trend, IoT Analytics forecasts that worldwide spending on datacentre infrastructure could approach one trillion dollars by the end of the decade, while Boston Consulting Group (BCG) projects US$1.8 trillion in total capital will be deployed by data centre players between 2024 and 2030. These staggering developments—especially the capital investment driven by Generative AI demand—have made infrastructure strategy a central priority for both hyperscalers and regional providers as they scramble to secure power and deploy high-density capacity.

Organisations are responding by placing greater emphasis on integrated facility design. “Power, cooling and white-space systems interact,” Albertazzi explains. “When you design them together, you create opportunities to improve efficiency and performance.”

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A shift toward system-level thinking As workloads grow heavier, organisations are reworking their approach to data-centre design.

Incremental add-ons no longer match the pace of technological change. Integrated engineering has become essential.

Albertazzi sees this shift as industry-wide. “Technology used in AI environments is higher density and has higher cooling demand and different electrical configurations,” he says. “Infrastructure planning now needs to consider these conditions from the start.”

The pressure is most evident in rack density. Traditional facilities operated between five and ten kilowatts per rack. Today’s cloud environments often exceed twelve kilowatts, while AI clusters regularly surpass one hundred kilowatts.

“We’re seeing cooling and power requirements that are completely different from what we saw even five years ago,” Albertazzi says. “And this trajectory is not slowing down.”

Forecasts indicate that nextgeneration silicon could push densities toward 250–300 kilowatts per rack, changing the thermal and electrical profile of entire facilities.

We are accelerating our innovation cycles. You cannot rely on the pace of the past when the technology requirements ahead of you are moving this fast

“Things are changing at a speed that is truly unprecedented in our industry,” he notes. “The technology roadmaps stretch multiple years out, and we work with partners like NVIDIA and other silicon providers to understand what those chips will require.”

This long-range planning shapes Vertiv’s engineering philosophy.

Albertazzi describes the importance of designing as complete systems rather than isolated components: “If you design a power train end to end, or a thermal chain end to end—from chip liquid cooling all the way to heat rejection—you have

opportunities to optimise the way the system works that do not exist if you just optimise one piece at a time.”

He adds: “While Vertiv will continue to strengthen individual point products, the system approach is becoming more and more important as the IT we serve becomes more challenging.”

Building infrastructure for the age of AI The rising complexity of data-centre environments has pushed Vertiv to expand its engineering footprint, this means faster innovation cycles

and more robust technologies that support dense, GPU-driven workloads. The company’s strategy now centres on delivering integrated systems that can be deployed faster and operated more efficiently across both hyperscale and regional facilities.

“We are accelerating our innovation cycles.

You cannot rely on the pace of the past when the technology requirements ahead of you are moving this fast.”

A central pillar of this strategy is VertivTM OneCore, the company’s pre-engineered, high-density platform designed to support next-generation silicon and multi-megawatt AI blocks. The goal is to give customers a repeatable, consistent approach to deploying advanced power and cooling systems across sites.

“VertivTM OneCore brings our thermal, power and white-space technology together in a standardised design. It reduces the engineering burden for customers and helps them deploy capacity in a more predictable way.”

VertivTM OneCore is a direct response to the pressures that operators now face: higher electrical loads, rapid thermal change, and the need to shorten deployment cycles without compromising reliability. The unified design allows Vertiv to deliver multi-megawatt prefabricated modules that align with the cooling and electrical envelopes of nextgeneration silicon. This also enables operators to scale in increments that match the growth of AI clusters, rather than relying on traditional build-out cycles that can take years.

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COVER FEATURE

“We see operators looking for ways to deploy faster while increasing resilience. VertivTM OneCore is designed to support both goals.”

A strategy built for scale Supporting this level of standardisation requires sustained engineering investment, and Vertiv has increased R&D spending accordingly. The company previously committed to growing its R&D investment by at least 15 percent year-on-year, but it is now exceeding that target as AI-related infrastructure becomes more complex. The focus areas include liquid cooling, advanced heat-rejection systems, intelligent power-train design, and predictive technologies that anticipate equipment behaviour under heavy load.

“We are continuing to expand our R&D because we see that it is absolutely central to our success and to enabling the infrastructure that AI requires.”

This investment is also reflected in strategic acquisitions. In August, the company acquired Great Lakes Data Racks & Cabinets, a US-based manufacturer known for high-density racks and enclosure systems. The acquisition expands Vertiv’s ability to support increasingly complex white-space environments, where the rack itself has become a critical engineering component as densities continue to rise.

In addition, Vertiv acquired Waylay NV, a Belgian software firm specialising in AI-driven automation, telemetry and real-time operational intelligence. The addition enhances Vertiv’s monitoring and predictivemaintenance portfolio, giving operators deeper insight into thermal and electrical behaviour as facilities run under heavier AI workloads.

Localisation is another pillar of Vertiv’s strategy, especially in regions where AI adoption, sovereigncloud policies and national digital programmes are driving an urgent need for high-density capacity.

Vertiv adapts its global portfolio to regional conditions and supports it with local manufacturing, in-country integration teams and long-standing 22

CXO INSIGHT MIDDLE EAST | DECEMBER 2025

channel partnerships. This enables advanced technology to be paired with operational models that suit the power availability, regulatory environment and deployment timelines of each market.

“We operate globally and locally.

Customers in different parts of the world have different requirements, and we make sure the technology is adapted accordingly.”

He notes that advanced technology developed in the US or Europe is made available in other regions— tailored for local regulations, climate and operating conditions.

The Middle East is a prime example of why this matters. Hyperscalers and local cloud service providers are expanding rapidly, sovereign-cloud frameworks are rising and AI capacity build-outs are accelerating across

Locality and globality need to work together seamlessly the Gulf. “Customers in the region are working at tremendous scale,” Albertazzi says. “They want globalclass technology delivered with local presence and local support.”

Vertiv’s localisation strategy in the Middle East is reinforced through its decades-long distribution partnership with MDS SI Group, one of the region’s most established technology

integrators. The partnership supports major data-centre developments across the Gulf by combining Vertiv’s global portfolio with MDS SI Group’s regional delivery capabilities.

“Locality and globality need to work together seamlessly,” says Albertazzi. “Strong regional partners allow us to execute with the speed and precision that large deployments demand.”

With execution strengthened and regional delivery expanding, partnerships upstream in the technology chain also shape Vertiv’s long-term approach. The company collaborates closely with silicon providers and hyperscalers to anticipate future requirements to enable infrastructure built today to remain ready for the next generation of compute.

“We see the value in anticipating the requirements of future silicon.

Our engineering teams work with technology partners to understand what upcoming chips will need in terms of thermal and electrical support.”

These relationships also extend to global co-location providers and emerging international operators, many of whom are expanding beyond their home regions.

“We operate in partnership with global and regional customers, and we make our global capabilities available to them as they expand.”

Looking ahead, Albertazzi expects several shifts to define the next phase of infrastructure development: broader adoption of liquid cooling, expansion of highvoltage power distribution within

white space, greater reliance on prefabricated multi-megawatt blocks and increasing use of predictive technologies to maintain operational stability. “We aim to stay ahead of what upcoming workloads will require,” he says. “Infrastructure has to keep moving with the technology.”

He summarises Vertiv’s long-term focus clearly. “We are designing, deploying and supporting systems that stand up to long-term operational demands. That is what our customers expect today.”

In a period defined by sustained compute growth and intensifying power and cooling demands, Vertiv’s strategy positions it as a central player shaping the next generation of digital infrastructure—building the systems that will carry AI and modern compute into its next phase.

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INTERVIEW

CHARGED WITH SCALE

Karim Azar, Area Vice President and General Manager for the Middle East at Confluent, on leadership priorities, market focus, and the operational realities of scaling real-time data infrastructure

A

cross the Middle East, enterprise data architectures are being tested in ways they were not designed for.

Governments are setting aggressive digital agendas, enterprises are modernising core systems under tightening regulatory constraints, and AI initiatives increasingly depend on whether data can move fast enough to support operational decisionmaking. In that environment, real-time data streaming has shifted from a specialist capability to foundational infrastructure.

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CXO INSIGHT MIDDLE EAST | DECEMBER 2025

Confluent provides an enterprisegrade data streaming platform designed to support continuous data movement at scale. Its technology underpins eventdriven architectures by ensuring that data produced by operational systems can be reliably consumed, processed, and governed across distributed environments. For enterprises operating across cloud, on-premises, and hybrid models, the platform enables systems to stay synchronised as events occur, rather than relying on batch-based

integration that introduces latency and operational friction.

That positioning reflects how modern enterprises increasingly treat data — not as something moved periodically for reporting, but as a live asset that supports digital services, analytics, and AI pipelines in real time.

Confluent’s platform has been built to operate at that layer, abstracting the complexity of managing streaming infrastructure while maintaining the controls enterprises expect in production environments.

For Karim Azar, recently appointed Area Vice President and General Manager for the Middle East, the challenge is less about market education and more about execution.

The region’s appetite for real-time systems is clear, but adoption varies sharply by market, industry, and regulatory environment.

“The way I look at the Middle East is that we are here to transform how we go to market and how we engage with customers and partners,” Azar says.

“My primary focus is to make sure we get as close as possible to both customers and partners — delivering a strong customer experience, service, and engagement.”

That focus on proximity shapes Confluent’s regional priorities. The UAE and Saudi Arabia anchor its near-term efforts. “The main idea is to double down on our efforts in the UAE, which is our home base, and also double down on KSA,” Azar explains, while ensuring that the wider region remain supported.

The sequencing is deliberate. Rather than spreading resources thinly, Azar wants execution models that can scale. “Once we focus on something, we need to make sure it becomes the gold standard so that it can be replicated elsewhere.”

Beyond the two largest markets,

Logen Wang / Shutterstock.com

Confluent is tracking momentum across Qatar, Oman, Kuwait, and Egypt — each with its own industry dynamics. Qatar’s national transformation agenda, Oman’s acceleration over the past two years, Kuwait’s sector-specific opportunities, and Egypt’s established partner ecosystem all factor into how the company approaches the region.

That ecosystem is central to Confluent’s operating model. While the company’s early work on Apache Kafka helped establish streaming as a core architectural pattern, Confluent today is focused on the realities enterprises face once streaming becomes production infrastructure.

Managed services, governance, security, and predictable operations matter as much as throughput and scale.

“I always say I’m a channel-first person,” Azar says. In the Middle East, trust is rarely built directly. “Some of our partners have been working with customers for 30, 40, or even 50 years.

They know their customers better than we do.”

For Confluent, partners are not a secondary route to market; they are how credibility is established. This is particularly true in sectors such as security and defence. “You cannot simply knock on doors,” Azar says.

“You need proper introductions through trusted people on the ground.”

Regional resellers, global system integrators, cloud service providers, and distributors form the backbone of that engagement model. It is also how Confluent navigates the region’s regulatory landscape. With data sovereignty requirements tightening across the Gulf, enterprises want cloud-native platforms that can still meet local hosting and compliance mandates. Confluent Cloud’s availability through regional hyperscaler data centres has become a practical requirement rather than a differentiator.

One area where Azar sees strong alignment between Confluent’s platform and regional priorities is the public sector. Historically, engagement has been cautious. That is changing.

“This is a sector you cannot and should not ignore,” he says. Across

We will be accessible and we will stay close to customers and partners

the UAE, Saudi Arabia, and Qatar, governments are setting technology frameworks rather than following private-sector adoption cycles. “With Vision 2030 and Vision 2040, the public sector is defining frameworks — including AI frameworks — rather than reacting to the private sector.”

State-backed initiatives such as Core42 in the UAE and large-scale digital programmes in Saudi Arabia illustrate that shift. For a platform designed to support real-time analytics and event-driven systems, public sector adoption is closely tied to national infrastructure strategies.

Azar’s leadership approach reflects that operational focus. He speaks less about vision statements and more about access, cadence, and accountability. “I want everyone to understand our priorities and the structure we’re putting in place on the ground,” he says. “We will be

accessible and we will stay close to customers and partners.”

Customer success, in his view, is defined by outcomes rather than deployments. “I want our customers to use Confluent’s products to accelerate their business, improve agility, reduce total cost of ownership in both the short and long term, and deliver tangible business value to their organisations.”

As enterprises across the Middle East move beyond experimentation, those outcomes are becoming harder to negotiate around. AI initiatives stall when data pipelines cannot operate in real time. Digital services fail when systems respond too slowly. In that context, data streaming becomes infrastructure that is expected to work continuously, without drawing attention to itself.

For Confluent, and for Azar, the regional task is execution-focused: build repeatable operating models, anchor them in trusted partnerships, and stay close enough to customers to understand how real-time data is actually being used.

“It’s about putting the right cadences in place, staying close to customers, and working closely with our channel ecosystem,” Azar says.

“That’s how customers stay informed about innovation and how we go to market.”

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INTERVIEW

AFTER THE PILOT

Kurt Muehmel, Head of AI Strategy, Dataiku, explores why enterprise AI success depends on how systems are governed, monitored, and designed to operate at scale

A

I has become a strategic priority for organisations across the region, with many racing to be early adopters. Yet being first does not always equate to success. Where do organisations most commonly struggle when moving from proof of concept to tangible business value?

Enterprise AI adoption today is largely defined by the rush to be an early adopter. Many organisations want to

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demonstrate progress — often to their boards — by showing that they are “doing AI,” and that instinct is entirely understandable.

The challenge is that proofof-concept initiatives are built to demonstrate possibility, not to support production-grade systems that organisations can depend on over time. Once the focus shifts from experimentation to deployment, an entirely different set of challenges emerges.

Production systems require deep, reliable connections to enterprise data rather than limited extracts.

They must be closely aligned with how the business actually operates.

Once deployed, these systems need continuous monitoring at scale, with transparency and traceability built in.

When issues arise, organisations must be able to understand exactly how the system behaved in order to address root causes, rather than applying superficial fixes.

Many organisations struggle because production deployment demands a fundamentally different mindset, approach, and toolset compared with pilots or POCs. Transparency is often cited as a critical success factor for enterprise AI. How important is it to design trust into AI systems from the outset?

It is essential. Trust at the level required to deploy AI at scale must be designed into systems from the beginning. Governance and oversight cannot be treated as an afterthought.

Trust depends on how data is selected, how models are chosen, and how those decisions are reviewed and validated. When governance is embedded into the design process, organisations can trust not only individual outputs, but the entire system used to design, develop, and deploy AI. At Dataiku, our focus is on ensuring that the system itself — effectively

the factory that produces AI solutions — is trustworthy, so the outcomes it generates can be trusted as well.

As governance and compliance requirements intensify globally, how does Dataiku help organisations manage this growing complexity without slowing innovation?

Organisations face significant pressure to move quickly while also dealing with uncertainty around evolving regulatory frameworks that are often fragmented across regions.

Dataiku provides built-in governance across the full AI lifecycle, while allowing organisations to tailor those processes to their specific needs. For example, organisations subject to the EU AI Act must classify applications based on risk. Dataiku enables customers to apply that framework in a way that reflects their region, use case, and industry.

Rather than enforcing a rigid, onesize-fits-all approach, we provide the tools organisations need to build governance systems that scale efficiently and work within their operational reality.

How should organisations think about balancing automation with human oversight as AI systems become more capable?

There is no single answer. It is best viewed as a sliding scale between fully manual and fully automated processes. Where that balance sits depends on the organisation, the application, and even the point in time.

Trust depends on how data is selected, how models are chosen, and how those decisions are reviewed and validated

Most organisations begin with a high degree of human oversight.

As trust builds through monitoring and governance, systems are gradually allowed to operate more autonomously. This is how enterprises move towards more autonomous AI — trust must be earned over time.

It mirrors how autonomy develops with junior employees: responsibility increases as consistency, reliability, and competence are demonstrated.

Is there an aspect of AI that you believe is overhyped — and something that is not receiving enough attention?

There is a widespread misconception about the capabilities of AI models, often driven by messaging from AI labs themselves. While these models are undeniably powerful, there is an overemphasis on the idea of imminent superintelligence.

That narrative can be dangerous. It encourages organisations to wait for the next model rather than addressing foundational challenges around data access, governance, and system design today. Organisations that adopt

a “wait and see” approach risk falling behind competitors who are doing the hard work now.

What is discussed far less is how different forms of intelligence — including agentic AI, predictive models, statistical intelligence, and human expertise — must work together. An excessive focus on large language models alone risks leaving significant value untapped.

Looking ahead, what should enterprises expect from the AI landscape over the next year — and where will Dataiku focus its efforts?

I expect 2026 to be the year in which AI agents mature and begin delivering real business value across complex, mission-critical processes.

That is where Dataiku is focused — working closely with customers and partners to build agent-based systems that can operate reliably at scale. Our product roadmap is aligned with providing organisations the capabilities they need to deploy agents across their most important business processes.

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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FEATURE

UNPACKED: TECH’S BIGGEST MOMENTS A roundup of key developments that made an impact on the technology industry in 2025

Skorzewiak / Shutterstock.com

2

025 marked a turning point in how technology is built, governed, and deployed.

The technology industry has entered a more consequential phase.

AI moved decisively into production.

Cloud strategies matured under cost, resilience, and sovereignty pressures.

Governments took on a more active role — not just as regulators, but as owners and architects of critical digital infrastructure.

Across global markets and the Middle East in particular, the year’s most significant stories shared common themes: access to compute became as important as innovation itself; outages and supply constraints exposed structural dependencies; and national priorities increasingly shaped technology decisions once left to the market.

What follows is a roundup of some of the most notable technology developments from across the year.

LANDMARK TECH DEAL Google plans to acquire Wiz Google announced plans to acquire cloud security firm Wiz for approximately $32 billion, marking one of the largest cybersecurity acquisitions on record. Founded in 2020, Wiz scaled rapidly by delivering agentless cloud security posture management across AWS, Microsoft Azure, Google Cloud, and Kubernetes, giving enterprises unified visibility into misconfigurations, identity risks, and cloud attack paths.

By 2024, the company had surpassed $350 million in annual recurring revenue, with customers spanning Fortune 500 enterprises and highly regulated sectors. Its ability to operate without agents and across multiple clouds has been central to its adoption as organisations contend with growing complexity and compliance demands.

The acquisition materially strengthens Google Cloud’s enterprise security portfolio, particularly in industries where continuous risk assessment and posture visibility are critical. Google has stated that Wiz will continue to support multi-cloud environments, preserving its neutrality across competing hyperscalers.

The transaction is expected to face regulatory review in the US and EU due to its scale, though it has been positioned as an infrastructure-level security move rather than market consolidation.

Honourable mention: HPE completed its $13.4 billion acquisition of Juniper Networks, consolidating networking, AI operations, and infrastructure capabilities under a single enterprise platform strategy.

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MAJOR NATIONAL AI INITIATIVE Saudi Arabia launches HUMAIN Saudi Arabia launched HUMAIN, a national AI company backed by the Public Investment Fund (PIF), as part of its Vision 2030 digital transformation strategy.

HUMAIN was established to develop sovereign AI models, national-scale compute infrastructure, and applied AI platforms for government and enterprise use.

The entity is designed to keep data, models, and compute within Saudi Arabia, aligning with national data sovereignty and cybersecurity requirements. HUMAIN is expected to partner with global hyperscalers, semiconductor companies, and AI vendors, while retaining ownership of strategic AI assets. The launch followed significant Saudi investment in data centres, cloud localisation, and AI skills programmes, positioning HUMAIN as the central execution arm of the Kingdom’s AI ambitions.

Honourable mention: The UAE AI Office and Google launched ‘AI for All’, a nationwide initiative delivering free training and awareness programmes to build AI skills across students, professionals, and communities by 2026.

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FEATURE

TOP TECH TREND Agentic AI takes centre stage In 2025, enterprise AI adoption shifted toward agentic AI systems capable of autonomously executing multi-step tasks across applications and workflows. Unlike traditional AI copilots that respond to prompts, these agents can plan, act, and iterate—interacting directly with enterprise systems, APIs, and data sources with limited human intervention.

Major technology vendors accelerated this shift. OpenAI expanded its Agents framework to support persistent, tool-using AI systems. Microsoft embedded autonomous agents across Copilot Studio and Dynamics 365 to handle tasks such as incident resolution and business process automation. Google Cloud advanced agent-based architectures through Vertex AI, while AWS positioned multi-agent orchestration as a core capability within its generative AI services. Enterprise software leaders including ServiceNow, Salesforce, and SAP introduced agentic workflows targeting IT operations, customer service, and finance.

Early deployments delivered measurable productivity gains but also exposed new risks, including error propagation, permission sprawl, and unclear accountability. As a result, enterprises placed growing emphasis on governance, security controls, and operational guardrails as agentic systems moved into production.

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KEY AI INFRASTRUCTURE PROJECT Tech titans unite to launch Stargate UAE In 2025, OpenAI confirmed plans to anchor part of its Stargate AI infrastructure programme in the UAE, in partnership with G42 and Microsoft, positioning Abu Dhabi as a strategic hub for frontier AI compute outside the United States. Stargate is a multi-year AI infrastructure initiative reported to involve investment at tens-of-billions-of-dollars scale, designed to support training and operation of next-generation AI models.

The UAE component of Stargate builds on G42’s role as a regional AI champion and Microsoft’s existing strategic investment and cloud partnership with G42. The project is expected to involve high-density GPU clusters, hyperscale data centre capacity, and longterm power planning, reflecting the physical demands of frontier AI development.

Honourable mention: The Microsoft–G42 partnership reached new heights in late 2025 with a $15.2 billion investment. This expansion includes a 200MW data centre project via Khazna, aiming to provide sovereign Azure-based AI infrastructure while skilling one million people in the UAE by 2027.

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Tada Images / Shutterstock.com

FEATURE

BIGGEST WORKFORCE SHIFT Tech layoffs amid AI boom Global technology firms continued to cut staff in 2025, but the pattern pointed less to contraction than redesign. Layoffs reflected a shift away from layered, generalist organisations toward leaner structures shaped by AI, automation, and long-cycle capital investment.

Intel executed the industry’s largest workforce reduction, cutting around 24,000 roles—nearly 22 percent of its employees—as it reset its operating model under CEO Lip-Bu Tan. The move was directly linked to Intel’s “foundry-first” strategy, aimed at challenging TSMC, with legacy layers stripped out to fund advanced manufacturing and its AI-optimised 18A process.

Amazon followed a similar logic at scale. In October 2025, the company confirmed the elimination of 14,000 corporate roles, roughly four percent of its global white-collar workforce.

AWS accounted for about half of the reductions, with engineers disproportionately affected as automation and agentic AI were introduced into coding, operations, and internal coordination.

By year-end, the restructuring extended into Europe, including significant cuts in Luxembourg.

Elsewhere, Google reduced headcount across hardware and recruiting, Meta continued targeted reductions outside AI, and Microsoft quietly reshaped teams as automation absorbed manual work.

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Hepha1st0s / Shutterstock.com

MOST VALUABLE MARKET SHIFT AI chips become the most valuable asset in tech Nvidia had firmly established itself as the most valuable company in the world, consistently trading at or near the top of global market-capitalisation rankings. While valuations fluctuated with daily market movements, Nvidia reached a historic peak of approximately $5.04 trillion in October 2025. By mid-December, its market capitalisation ranged between $4.2 trillion and $4.6 trillion, frequently placing it ahead of Apple (around $4.1 trillion) and Microsoft (around $3.8 trillion).

Nvidia’s ascent was driven by sustained demand for AI accelerators and GPU-based computing, as hyperscalers, data-centre operators, and enterprises expanded infrastructure to support large-scale AI training and inference. The company’s data-centre business became its primary growth engine, with GPU

platforms such as Hopper and Blackwell widely adopted for large language models, generative AI workloads, and high-performance computing.

Beyond chips, Nvidia expanded its role from component supplier to infrastructure provider. The company pushed its “AI factory” model, delivering integrated, liquid-cooled rack-scale systems such as the GB200 NVL72, designed to operate as a single, unified supercomputer.

Honourable mention: AMD and Broadcom also saw significant gains—with AMD surpassing a $400 billion market cap for the first time in 2025. However, none have yet challenged the sheer scale of Nvidia’s valuation or its 70 percent+ control of the advanced AI chip market.

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Michael Vi / Shutterstock.com

FEATURE

BIGGEST DISRUPTION AWS global outage In October 2025, Amazon Web Services experienced a global outage linked to DNS resolution failures, impacting multiple AWS regions and services.

The disruption affected application hosting, identity services, and third-party platforms that rely on AWS infrastructure. Thousands of businesses experienced service degradation or downtime.

AWS confirmed the issue stemmed from internal DNS configuration failures that caused cascading effects across dependent services. While most services were restored within hours, the incident triggered renewed scrutiny around single-cloud dependency, resilience planning, and multi-region architecture for mission-critical workloads.

Honourable mention: A global PlayStation Network outage disrupted online gaming and digital storefronts worldwide.

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KEY CLOUD SHIFT The rise of sovereign cloud in the Middle East In 2025, enterprise and government cloud strategy in the Middle East shifted decisively toward sovereign cloud models, driven by data residency laws, cybersecurity mandates, and national AI ambitions. Sovereign cloud refers to infrastructure where data, encryption keys, operational control, and governance remain within national jurisdiction.

The UAE emerged as an early mover, becoming one of the first countries globally to operationalise sovereign cloud at scale. du’s National Hypercloud provided a nationally governed cloud platform that allows government entities to consume hyperscaler-grade services while retaining full data residency and regulatory control, positioning it as foundational infrastructure for public sector digital services. In parallel, e& enterprise’s UAE Sovereign Launchpad, developed with AWS, extended sovereign cloud access to regulated industries, combining in-country hosting, customer-controlled encryption, and compliance-aligned operations to support advanced AI, analytics, and mission-critical workloads.

In Saudi Arabia, sovereign cloud adoption expanded in line with Vision 2030, supported by telecom-led platforms, localised hyperscaler regions, and national cybersecurity frameworks. Similar deployments advanced in Qatar and Oman through government-backed digital programmes.

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SPOTLIGHT

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RUNNING THE

NEW FRONTIER

AWS hosted its annual re:Invent conference in Las Vegas, bringing together cloud leaders, engineers, and senior technology decision-makers from around the world to examine what it takes to operationalise AI at scale

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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SPOTLIGHT

A

WS re:Invent returned to Las Vegas, bringing together tens of thousands of cloud leaders, engineers, and enterprise executives for a week of technical sessions and strategy updates. It’s a familiar rhythm for the industry—one of the most watched checkpoints in the enterprise technology calendar.

AWS enters this year’s event with an expanded footprint and a sharpened focus. The company has reached $132 billion in annual recurring revenue, and its infrastructure now supports the majority of the world’s largest organisations. More than 90 percent of Fortune 100 companies—and most of the Fortune 500—use AWS for cloud, security, analytics, and AI workloads, a reminder of how deeply embedded the platform has become in global enterprise operations.

Against this backdrop, Matt Garman, CEO at Amazon Web Services (AWS) delivered his muchanticipated re:Invent keynote. His opening remarks cut directly to the moment the industry finds itself in.

“Every single customer experience, every single company, frankly every single industry is in the process right now of being reinvented,” he said.

“We’re still in the early days of what AI is going to deliver.”

Garman acknowledged the gap many enterprises continue to feel between AI’s promise and the returns they are seeing. “When I speak to customers, many of you haven’t yet seen the returns that match up to the promise of AI,” he said. “The true value of AI has not yet been unlocked.”

Throughout his keynote, he returned to the same theme: how AI is deployed matters as much as the models themselves. “AI assistants are starting to give way to AI agents that can perform tasks and automate on your behalf,” Garman said. “This is where we’re starting to see material business returns.”

He also spoke about the scale he expects agentic systems to reach.

“I believe that in the future, there’s going to be billions of agents inside of every company and across every imaginable field.”

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Capability to execution The announcements that followed reflected the areas AWS chose to spend time on this year. Across infrastructure, software, and tooling, the focus stayed close to what happens once AI systems are expected to operate continuously inside the enterprise.

AWS expanded its AI compute roadmap with new Trainium-based systems designed for large-scale training and inference workloads, while continuing to support Nvidiapowered platforms. The approach

reflects how many enterprises are thinking about AI infrastructure— balancing performance, cost control, and flexibility rather than committing to a single path.

That pragmatism carried into the introduction of AWS AI Factories.

Designed for organisations with strict regulatory, sovereignty, or latency requirements, the offering brings AWS-managed AI infrastructure into on-premises environments.

For many enterprises, particularly in government, finance, and critical industries, the conversation around

AI increasingly centres on where workloads run as much as how they perform.

On the software side, Amazon Bedrock continued to take shape as AWS’s centre of gravity for generative and agentic AI. Updates focused on orchestration, governance, and visibility—areas that come into sharper focus once AI systems begin interacting with production data and applications. AWS also expanded its Nova family of foundation models and introduced Nova Forge, allowing organisations to customise

models using proprietary data without managing training pipelines themselves.

AWS also introduced a set of Frontier Agents, including Kiro, an autonomous development agent capable of planning, coding, testing, and deploying software, alongside agents focused on security and operations. Rather than positioning these as replacements for existing teams, AWS described them as systems designed to sit inside established workflows and take on work that already exists.

Across sessions and briefings, the emphasis remained consistent: AI systems are being built to run, not to demo.

Building without friction Those themes carried into the keynote from AWS Vice President for Agentic AI, Swami Sivasubramanian, where the focus shifted from strategy to construction.

“We are living in times of great change,” he said. “Agents give you the freedom to build without limits.”

Swami spoke about reducing

SPOTLIGHT

The true value of AI has not yet been unlocked MATT GARMAN AWS

Swami Sivasubramanian, VP for Agentic AI, AWS

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friction for developers and organisations working with increasingly autonomous systems.

“In this new world, we believe how you build agents should be really simple,” he said, describing AWS’s efforts to abstract complexity while preserving enterprise-grade controls.

He was careful to frame the week’s announcements as part of a longer journey. “Everything we’re showing is just the beginning of what’s possible with AI,” Swami said. “With every step we are making it easier for anyone to build.”

Throughout his keynote, governance surfaced repeatedly— not as a constraint, but as a requirement once AI systems move beyond experimentation. Policy enforcement, observability, and control featured heavily, reflecting how enterprise adoption unfolds when AI becomes part of daily operations.

The Renaissance Developer Every year, one of the most anticipated moments of AWS re:Invent is the closing keynote from Amazon.com CTO Werner Vogels. This year, that session carried a different weight. Early in his address, Vogels acknowledged that it would be his final re:Invent keynote after more than a decade on the main stage.

“This is my final re:Invent keynote,” Vogels said, before quickly clarifying that he is not leaving the company. “I think that after 14 re:Invents you guys are owed young, fresh, new voices.”

Vogels spent the rest of the session focused squarely on developers and the changing nature of their work, speaking for more than an hour to a packed room before signing off with a simple “Werner, out” and a literal mic drop.

At the centre of his keynote

Werner Vogels, CTO, Amazon.com

was a question he said he hears repeatedly. “Will AI take my job?”

“Maybe,” he replied, to cautious laughter, before reframing it more pointedly. “Will AI make me obsolete?”

“No — if you evolve.”

Vogels grounded that answer in experience. “I’ve seen first hand how people can evolve, given the right tools — just look at Amazon,” he said, before walking through major shifts in computing over the past five decades.

“Our tools today are extraordinary,” Vogels said, “but none of this removes the work that only you can do.”

That emphasis on responsibility surfaced throughout his remarks.

“Remember, the work is yours,” he told the audience. “Not that of the tool’s... it’s your work that matters.”

‘Will AI make me obsolete?’ No — if you evolve WERNER VOGELS AMAZON.COM

Despite the pace of change, Vogels remained optimistic. “There’s never been a time to be more excited about being a developer,” he said, referencing Jeff Bezos’s view that further “Golden Ages” still lie ahead. “Progress in one field accelerates progress in other fields.”

To frame that optimism, Vogels drew a parallel with the Renaissance—a period shaped by

curiosity, better tools, and people willing to work across disciplines.

From scientific advances to the invention of the pencil, progress followed when individuals expanded how they thought and worked.

From that comparison came his idea of the Renaissance Developer.

“These qualities are just as important today,” Vogels said.

Curiosity sat at the centre of that model. Curiosity leads to learning, and learning leads to invention.

Experimentation follows, along with a willingness to fail—even Leonardo da Vinci failed, Vogels reminded the audience.

“Learning is social,” he added, encouraging developers to engage beyond their comfort zones. He spoke about recent trips to Africa and South America, including his first visit to the Amazon rainforest, as reminders of the real-world problems technology can help address.

Systems thinking formed another pillar of his framework. “As structure changes, behaviour changes — and when feedback changes, outcome changes,” Vogels said, using an ecological example from Yellowstone National Park.

Communication came next. The ability to express ideas clearly— between people and between humans and machines—reduces ambiguity. “Specifications reduce ambiguity,” he noted.

Ownership completed the picture.

Vogels cautioned against unexamined “vibe coding,” pointing instead to verification debt and hallucination as challenges developers increasingly face. Progress, he said, is coming through automated reasoning, testing, and specification-driven development.

“This is how we transfer knowledge and how we grow the next generation of builders,” Vogels said, pointing to code reviews as a critical learning mechanism.

The final quality of a Renaissance Developer, he concluded, is polymathy—depth paired with breadth. He contrasted narrow specialisation with T-shaped expertise, arguing that understanding across disciplines increasingly matters.

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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VIEWPOINT

in the last two years, resulting in significant revenue losses. Such disruptions not only impact finances but also erode trust and hinder future opportunities.

The shift to AI-native secure networking

FUTURE-READY NETWORKS:

A STRATEGIC IMPERATIVE, NOT A COST

By Mohannad Abuissa, MD of Solutions Engineering and CTO, Cisco META, Romania and CIS

T

he UAE is one of the few nations with both the ambition and the agility to implement AI at national scale. National programs and partnerships, including secure, end to end AI infrastructure initiatives led by players such as G42, are accelerating adoption across sectors.

The Cisco AI Readiness Index 2025 reveals that many UAE organisations are moving AI from pilots to production, with 23 percent have finalised their AI use cases and 17 percent possess a mature innovation process for their AI use cases. The question is no longer whether to adopt AI but how to operationalise it at scale with security

and measurable impact. That starts with an infrastructure first approach that unifies compute, data and the network to support real workloads.

However, as adoption accelerates, existing architectures struggle to deliver the scale, low latency and resilience real workloads require.

According to Cisco AI Readiness Index 2025, only 39 percent of UAE organisations say their infrastructure and data environments are ready for AI. To move beyond pilots, enterprises need modernised, AI native networking as the foundation for competitiveness.

Infrastructure demand is rising

The critical demand for AI-ready networking is underscored by Cisco’s 2025 networking research, where a staggering 94 percent of IT leaders expect AI, IoT, and cloud to profoundly impact networks. This necessitates an evolution from static infrastructures to dynamic, intelligent frameworks designed for complex AI workloads.

While AI workloads require vast amounts of bandwidth, ultra-low latency and the ability to adapt in real-time to fluctuating demands, all while remaining resilient; these are unique challenges that traditional architectures cannot meet.

Overlooking these requirements may result in substantial drawbacks.

According to Cisco’s networking research 77 percent of IT leaders reported experiencing major outages

AI-native networking offers a transformative approach, prioritising automation, observability, and energy efficiency. These features are vital for digital competitiveness, streamlining operations, enhancing visibility, and addressing sustainability by optimising resource use and reducing carbon footprint.

Also, as cyber threats become increasingly sophisticated, networks must act as the first line of defence.

Cisco Networking Research 2025 shows that 97 percent of UAE IT leaders believe an improved network will enhance their cybersecurity posture. AI-native networks go further than enhancing operational efficiency; they better safeguard data, applications and consequently reputation.

The business impact

Robust AI-ready networks yield substantial economic benefits, driving revenue growth and operational efficiency. According to Cisco AI Readiness Index 2025, over half of UAE leaders anticipate AI tools will significantly impact revenue, with 69 percent of UAE organisations already reporting gains in profitability, productivity, and innovation from AI adoption.

Recognising this, 91 percent of IT leaders plan to increase networking budgets, viewing it as a strategic investment to fully leverage AI, not merely a cost.

Beyond IT: Networking as a strategic business imperative

Prioritising AI-ready networking is crucial for organisations and policymakers alike. The network has evolved beyond a mere IT concern to become a strategic asset shaping future economies and enterprises.

Investing in flexible, intelligent, and secure networks unlocks AI’s full potential, drives efficiency, and ensures a sustainable competitive edge in the rapidly evolving digital landscape.

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

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VIEWPOINT

THE NEW CYBERSECURITY REALITY

By Ezzeldin Hussein, Regional Senior Director, Solution Engineering, META, SentinelOne

A

s more enterprises adopt AI, security leaders are now faced with a more complex reality. 2026 will push them to rethink accountability, identity verification, intelligence sharing, and platform strategy. With attackers moving at a fast pace and AI expanding across businesses, the traditional process can no longer keep up. To mitigate risks, enterprises should rebuild the core foundations of their cybersecurity strategy.

Accountability cannot be automated

AI agents can perform procedural work that security teams traditionally handled. This shift is inevitable and beneficial, but we humans remain responsible for the outcomes of automated systems. Reviewing the work of thousands of AI agents is impossible with traditional alerts.

Instead of drowning security analysts in fragmented signals, organisations need systems that unify related alerts and tasks into common decision points. This will create a “Goldilocks spot” that pairs high automation with human responsibility. Analysts can then make a single auditable decision rather than hundreds of inconsistent, smaller ones. This preserves oversight while fully benefiting from AI’s consistency, breadth, and speed.

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The deepfake defence paradox

Deepfakes have advanced to the point where attackers can convincingly replicate a person’s image, voice, or behaviour at minimal cost. This should concern CISOs, as video and voice communications are heavily compressed, making it difficult to differentiate between real and manipulated content. Many companies still think detection systems can handle this issue.

When a detection system flags a fake, it also teaches attackers how to refine their methods. This creates a dangerous feedback loop where attackers can keep trying endlessly until they succeed. In 2026, the most resilient enterprises will move beyond single-layer detection and adopt multi-factor, out-of-band verification methods that operate entirely outside the communication channel. We see early examples of this in consumer technologies such as iOS Contact Key Verification. Enterprises will need similar models to verify identities.

Detection remains essential, but the verification process needs to evolve.

Collective security at the core of enterprise defence

For years, organisations have benefitted from the intelligence shared by their security vendors.

Yet, many enterprises decide to share information only after something happens. This limits the collective gain. Cyber-attackers do not operate alone. They share insights, techniques, and tools, thereby creating a global network.

Defenders must think and have the same collective mentality to protect their data. In the coming year, enterprises will comprehend that selective intelligence sharing makes everyone’s defences stronger, including their own. The challenge is to implement this while protecting sensitive data and still surfacing crucial signals.

As customer comfort grows and as platforms evolve to support data sharing more securely, the industry will move toward a more interconnected model. This model

Cyber-attackers do not operate alone.

They share insights, techniques, and tools, thereby creating a global network will be more collective as the safety of one truly becomes the safety of all.

The end of security silos

Cybersecurity has been facing the hurdle of fragmented architectures, defined by acronyms and isolated

point solutions. Identity security, endpoint protection, UEBA, and CTEM evolved separately while relying on the same underlying machinery. This can cause gaps that attackers can easily target.

Large-scale AI platforms already give us an idea of what the future holds. They present a single interface capable of executing various operations that once required multiple tools.

2026 will see enterprises actively move towards a unified security ecosystem, breaking boundaries between products. Instead of worrying about which tool to pick, organisations should focus on the outcomes they want to achieve.

A unified platform will make this possible, where teams can see activities and alerts and be

able to act on them quickly. This approach will enhance visibility, reduce operational complexity, and eliminate gaps.

Looking ahead

The year ahead will challenge every organisation to reevaluate its assumptions. AI will continue to transform both offense and defence, while the rise of deepfakes will necessitate new models of trust. Intelligence sharing will become necessary. Security platforms will develop from fragmented systems and adopt a unified approach. Organisations that are clearly and intentionally prepared to accept these changes will reduce risk and lay the groundwork for secure growth in the digital landscape.

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INTERVIEW

SECURING THE DIGITAL MOMENTUM Steve Riley, Field CTO at Netskope, discusses how SASE and Zero Trust are reshaping enterprise security to balance innovation, governance, and control

U

AE organisations are advancing digital transformation while facing tighter data protection and residency requirements. How are you seeing enterprises balance innovation with compliance in this environment?

The United Arab Emirates is advancing its digital economy with clear objectives, including a national strategy to establish a fully digital government by 2025. This rapid digital progression introduces a complex challenge for enterprises: they must adopt new technologies while also adhering to strict data

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protection and residency laws.

Organisations are addressing this by integrating compliance into the initial design of their digital projects, moving beyond treating it as a secondary consideration.

As AI reshapes how businesses think about security, what new risks should enterprises keep in mind?

The integration of artificial intelligence into business operations introduces new considerations for governance and accountability. As AI systems manage more data and decision-making, the potential for new risks increases, including AI

systems that could be tricked by clever attacks, leading to data leaks.

Businesses are responding by developing specific guidelines for AI use, focusing on transparency in how algorithms function and establishing clear accountability for automated outcomes. This approach helps manage the potential for unintended consequences from AI adoption.

With data visibility and movement now a board-level concern, how is this shifting the conversation between CISOs and business leaders?

Data visibility has become a priority

Steve Riley, Netskope

at the board level. Chief information security officers are now involved in strategic discussions, explaining technical risks in terms of business impact, such as financial loss or reputational damage.

This shift has transformed the dialogue between security leaders and executives, focusing on how data control supports broader business objectives like customer trust and market expansion.

Every security leader faces the dilemma of trying to strike the right balance between staying secure and getting work done. Extremes on either end introduce risk. A modern platform like SASE offers controlled data flow in ways that enable the business while minimising risk.

All IT departments must transition from being the “Department of No” to the “Department of Know.”

SASE provides an adaptive security architecture that gives IT what it needs to know — environmental signals and threat intelligence — so that IT can stop saying no. Matching the level of access to the context in which that access occurs offers exactly the right balance. SASE is the opposite of a security barrier; it is a business enabler.

Dozens of point products are

Every security leader faces the dilemma of trying to strike the right balance between staying secure and getting work done likely to be plagued by configuration errors and misalignments, especially where functionality overlaps.

SASE reduces risk by eliminating overlapping controls, maintaining consistent administrative paradigms across its various functions, and exchanging signals and context with related platforms such as identity management and endpoint protection.

From a Netskope standpoint, how does SASE help enterprises simplify that complexity — and what’s different about the way you approach it?

The main complexities are administrative and organisational, not

technical. The prerequisites for an effective zero trust strategy include defining roles and assigning them to personas that carry common access requirements, identifying all applications and mapping how they exchange information among themselves and with external resources, and documenting certain aspects of every information asset, including location, sensitivity, function, and lifetime.

These are necessary to construct policies that grant the right access by the right people to the right resources at the right times for the right reasons.

What sets Netskope apart is its focus on real-time data inspection, which works well in diverse environments like those in the region.

An effective zero trust strategy also involves cooperation between stakeholders.

Perhaps the main technical challenge is gathering the signals and the context for the kinds of five-rights-based policies that are essential to an effective zero trust strategy. When deployed well — after companies address the prerequisites and foster effective communications — a good SASE provides exactly the necessary signals and context, significantly reducing the likelihood that a breach might occur.

Looking ahead, what do you see as the next frontier for enterprise security in the region, and what role will Netskope play?

The next phase of enterprise security in the region will likely involve greater use of AI to predict and address threats before they cause harm. There will be a stronger emphasis on context-driven access, sovereign cloud controls, and deeper integration between security and networking.

Netskope’s continued investment in regional infrastructure supports this shift, helping enterprises adopt these capabilities without adding complexity. The company’s approach of combining security with networking functions in a unified platform is expected to remain relevant as organisations look for simpler ways to manage increasingly complex digital environments.

DECEMBER 2025 | CXO INSIGHT MIDDLE EAST

47

BLOG

AFTER THE RUSH Sunil Paul, Co-Founder and MD at Finesse, reflects on how enterprise AI adoption in 2025 moved from urgency to operational reality, and what that shift means for 2026

A

s 2025 comes to a close, most enterprises have moved well beyond debating whether artificial intelligence belongs in their organisation. AI systems are live, increasingly relied upon, and embedded across customer engagement, operations, and decision-making. What changed over the course of the year was not enthusiasm, but awareness.

Much of the activity during 2025 was driven by urgency. Organisations were under pressure to demonstrate momentum, and AI became a visible signal of progress. Investment flowed rapidly into cloud capacity, data platforms, specialised tooling, and

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CXO INSIGHT MIDDLE EAST | DECEMBER 2025

skills, often in parallel across teams.

At the same time, more advanced capabilities began moving into production. Agentic AI systems, designed to plan, act, and adapt with limited human intervention, started to make tangible progress beyond research environments. Their potential is significant, but so are the expectations they place on reliability, oversight, and operational discipline.

Spending patterns reflect this acceleration. Gartner estimates global AI-related spend reached close to US$1.5 trillion in 2025, spanning software, infrastructure, and services. Enterprise investment in generative AI rose sharply, from roughly US$11.5 billion in 2024 to

around US$37 billion in 2025. Yet despite this scale of investment, global surveys continue to show that only a smaller proportion of organisations are consistently capturing value at scale. The gap between deployment and durable outcomes remains pronounced.

As the year progressed, it became evident that moving AI into everyday operations changes the nature of the challenge. Once AI systems are depended upon rather than tested, questions of capacity, resilience, control, and long-term availability move to the forefront. What began as an enterprise-level concern around scale and sustainability quickly becomes broader in scope when AI is expected to support entire sectors, public services, and national priorities.

It is in this context that the shift has also played out at a national level. Governments have doubled down on AI as a strategic priority, committing to largescale infrastructure and sovereign capabilities designed to support long-term, dependable use.

Initiatives such as Stargate UAE, anchored by Abu Dhabi’s G42 and OpenAI, and HUMAIN, Saudi Arabia’s national AI programme, reflect this intent.

This matters for the region because AI adoption here is closely tied to economic diversification and modernisation.

As AI becomes a shared foundation across sectors, its design and operating discipline start to shape how easily those sectors can grow. When systems are difficult to manage or scale, progress slows. When they are built with longevity in mind, they support sustained development.

Looking ahead to 2026, a more measured phase is emerging.

Enterprises are becoming more selective, prioritising simplification, reuse, and shared foundations over unchecked expansion. AI has now joined the ranks of core enterprise systems. Treating it with the same intent and longterm thinking will determine who sustains momentum in the years ahead.

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For enquiries Merle Carrasco Commercial Director, Insight Media & Publishing M: +971 55 118 1730 E: merlec@insightmediame.com

WHAT’S NEW

SEAGATE: Exos 4U100 and 4U74 JBOD

HUAWEI: Watch Ultimate 2

Huawei has introduced the Watch Ultimate 2, expanding its premium smartwatch portfolio with a focus on durability, outdoor use, and advanced health monitoring.

The Watch Ultimate 2 features a 1.5-inch LTPO 2.0 AMOLED display protected by sapphire glass, housed in a zirconium-based liquid metal case with a ceramic bezel.

The watch is engineered for extreme conditions, supporting professional diving up to 150 metres, with a multi-layer water-resistant structure

and an integrated depth and pressure monitoring system.

A key addition is sonarbased underwater messaging, allowing divers to exchange preset text messages and alerts while submerged.

The watch also includes safety functions such as dive tracking, ascent warnings, and emergency alerts.

For health monitoring, the Watch Ultimate 2 introduces Huawei’s TruSense system, combining wrist-based sensors with a dedicated X-TAP sensor for fingertip measurements.

It supports ECG, heart rate, blood oxygen, skin temperature, stress tracking, and comprehensive health reports through Huawei’s Health Glance feature.

The device includes dualfrequency, five-system GNSS for improved positioning accuracy and supports outdoor modes such as expedition, golf, and hiking.

Connectivity options include eSIM support, while battery life extends across multiple days depending on usage mode.

The Huawei Watch Ultimate 2 is positioned for users seeking a rugged smartwatch with advanced health, diving, and outdoor capabilities.

KIOXIA: Exceria Basic SSD

KIOXIA has expanded its consumer storage portfolio with the launch of the Exceria Basic SSD Series, targeting everyday PC and laptop users seeking a straightforward performance upgrade.

The Exceria Basic series uses a PCIe 4.0 NVMe interface, offering a significant step up from SATA and PCIe 3.0 drives 50

CXO INSIGHT MIDDLE EAST | DECEMBER 2025

Seagate has launched its latest edge and enterprise storage platforms, introducing the Exos 4U100 and Exos 4U74 JBOD systems to address growing data demands across data centres and distributed edge environments.

The new platforms are designed to deliver high-density storage in a compact 4U enclosure, with the Exos 4U100 supporting up to 3.2 petabytes of raw capacity in a single chassis. The systems are built to scale large datasets generated by AI, machine learning, analytics, and edge workloads, where data volumes continue to expand rapidly.

Both platforms support SAS-4 connectivity and are compatible with SAS and SATA drives, offering flexibility for different enterprise deployment models. The architectures are optimised for performance, reliability, and operational efficiency, with improved airflow and cooling to support dense configurations in space-constrained environments.

The systems also incorporate enterprise management and security features, including secure boot capabilities and support for Redfish-based management, enabling standardised monitoring and integration into modern data centre operations.

Seagate’s latest edge and enterprise storage platforms are aimed at organisations seeking to consolidate large volumes of data while maintaining performance and efficiency across core and edge infrastructure. The launch reflects the increasing need for scalable, high-capacity storage as datadriven workloads continue to grow.

commonly found in older systems. According to KIOXIA, the SSD delivers sequential read speeds of up to 7,300 MB/s and write speeds of up to 6,800 MB/s, making it suitable for faster boot times, quicker application launches, and smoother file transfers.

The drive is available in capacities of up to 2 TB and comes in the widely adopted M.2 2280 form factor, ensuring compatibility with most modern desktops and notebooks that support PCIe 4.0. It is designed for general-purpose computing, including everyday productivity, content consumption, and light creative workloads.

Exceria Basic joins KIOXIA’s broader Exceria SSD lineup, which also includes the Exceria Plus and Exceria Pro series, allowing users to choose storage options based on performance and usage needs.

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OT

Detects malicious code and prevents data breaches across laptops, desktops & mobile devices.

Protects workloads, applications and data.

Provides specialized protection for OT environments

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